An Autonomy Evaluation Method of UUV for Acoustic Environment and Situation Awareness

The core capability of sonar equipment used by unmanned underwater vehicle (UUV) is embodied in the autonomy of signal processing. Aiming at the lack of autonomy evaluation system for unmanned sonar, this paper quantitatively evaluates the autonomy level and constructs an autonomy grading model for acoustic environment and situation awareness. The model mainly includes: levels of autonomy, autonomy level indicators and autonomy level evaluation method 3 parts. Firstly, the model constructs a composite index evaluation system based on the degree of artificial intervention and machine learning ability. The analytic hierarchy process is used to determine the weight of the multi-class core indicators. And the fuzzy comprehensive evaluation method is used to combine the score and weight of each indicator to obtain the final score, which is matched with the score interval to specify the autonomy level. Finally, the practical cases are used to analyze and verify the rationality of the grading model. This model quantifies the process and results of the autonomy evaluation of UUV sonar signal processing.